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Questions and Answers
What characteristic does a hypothesis NOT typically possess?
Which of the following statements describes a one-directional hypothesis?
In the context of hypotheses, what does the term 'positive relationship' mean?
What is true about two-directional hypotheses?
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Which characteristic is essential for a hypothesis to be useful?
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What type of variable is manipulated by the researcher?
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Which of the following is true regarding a continuous variable?
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What distinguishes a ratio measure from other levels of measurement?
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Which of the following is an example of a nominal measure?
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In which level of measurement can you say that one response is more or less than another?
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What is a characteristic of a qualitative variable?
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What defines a dependent variable?
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Which level of measurement implies that the distance between attributes has meaning?
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What best defines a concept?
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Which of the following is an example of a concrete concept?
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What is the term used for a representation of a concept that can vary?
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During conceptualization, what is primarily established?
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What is operationalization in research?
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Which of the following would NOT be a variable regarding political participation?
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What must be ensured about variable attributes in research?
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What aspect should researchers consider when selecting variable attributes?
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What does reliability in measurement refer to?
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Which type of validity assesses whether a measure is predictive of an external criterion?
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How is face validity described in relation to a measurement?
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What might indicate low construct validity?
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What does content validity measure in research?
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Why might qualitative research methods be seen as having lower reliability?
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Which statement best captures the essence of validity in measurement?
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What is a potential issue with a measure that is considered reliable but not valid?
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Study Notes
Concepts
- A concept is a general idea used to summarize a specific phenomenon
- Concepts can be concrete, abstract, tangible, or intangible
- Examples of concepts include "height" and "love"
Transferring Concepts into Measurable Variables
- A variable represents a concept in its variation of degree, varieties, or occurrence
- A variable is a characteristic of a thing that can assume varying degrees or values
- Most variables are truly variable, meaning they have multiple categories or variations
Example: Concept and Variable
- Political participation is a concept
- Variables related to political participation include:
- Voted or not
- How many times a person has voted
- What party a person votes for
Conceptualization
- The process of conceptualization involves defining the meaning of a concept
- Conceptualization involves moving between loose ideas and finding a word that best describes them
- Sometimes, new terms need to be created to encompass a concept
- Dimensions represent subgroups of a concept
Operationalizing Choices
- Operationalization is the process of converting concepts into measurable terms
- It involves developing research procedures that result in empirical observations
- For example, socioeconomic status (SES) can be operationalized by combining income and education levels
Variable Attribute Choices
- Variable attributes must be exhaustive and exclusive
- They represent the full range of possible variations
Degree of Precision
- The level of precision in variable attributes depends on the research interest
- Consider whether it is better to include too much or too little information in a variable
Variables
- The dependent variable is the variable that is measured by the researcher
- The independent variable is the one that the researcher manipulates
- For example, in a study about the effects of a new educational program, the program is the independent variable and student achievement is the dependent variable
Qualitative and Quantitative Variables
- Qualitative variables are composed of categories that cannot be compared in terms of magnitude
- Quantitative variables can be ordered with respect to magnitude on some dimension
- Continuous variables are quantitative variables that can be measured with an arbitrary degree of precision
- Discrete variables are quantitative variables where values can differ only by well-defined increments
Levels of Measurement
- Nominal
- Ordinal
- Interval
- Ratio
Nominal Measures
- Offer only a name or label for a variable
- There is no ranking involved
- They are not numerically related
- Examples include gender and race
Ordinal Measures
- Variables with attributes that can be rank-ordered
- One response can be considered more or less than another
- The distance between attributes lacks meaning
- An example is socioeconomic class (lower, middle, upper)
Interval Measures
- The distance separating attributes has meaning and is standardized
- A "0" value does not mean the variable is not present
- An example is a score on an ACT test
Ratio Measures
- Attributes have a "true zero point" which has meaning
- Examples include waist and biceps measurements
- Allows for the creation of ratios
Hypotheses
- Hypotheses are untested statements that specify a relationship between two or more variables
- An example is "Milk drinkers make better lovers"
Characteristics of a Hypothesis
- States a relationship between two or more variables
- Is stated affirmatively
- Can be tested with empirical evidence
- Most useful when it makes a comparison
- States how multiple variables are related
- Has a logical explanation for the relationship
Positive and Negative (Inverse) Relationships
- Positive: as values of independent variable increase, the values of the dependent variable increase
- Negative: as values of independent variable increase, the values of the dependent variable decrease (or vice versa)
Two-Directional Hypotheses
- General expression of a hypothesis
- Suggests that groups are different or concepts are related, but without specifying the direction of the difference
- An example is "Men and women trust UK security differently"
One-Directional Hypotheses
- Specific expression of a hypothesis
- Specifies the precise direction of the relationship between the dependent and independent variables
- An example is "Women have greater trust in UK security compared to men"
Determining Quality of Measurement
- Accuracy and consistency in measurement are essential
- Validity refers to accuracy
- Reliability refers to consistency
Reliability
- The extent to which the same research technique applied to the same object will give the same results
- Reliability does not ensure accuracy, as a measure can be reliable but inaccurate due to bias in the measure or data collection
Validity
- The extent to which a measure reflects what we think or want it to be measuring
Face Validity
- The measure seems to be related to what we are interested in finding out, even if it doesn't fully encompass the concept
- Example: Using grades to measure intellectual capacity has high face validity, while using number of close friends has low face validity
Criterion Validity
- The measure is predictive of some external criterion
- Example: ACT scores have high criterion validity as they potentially predict success in college
Construct Validity
- The measure is logically related to another variable as conceptualized
- Example: Financial stability might not be strongly related to happiness, resulting in low construct validity when used to measure happiness
Content Validity
- How much a measure covers a range of meanings, and whether it covers all relevant dimensions
- Example: A measure of prejudice that only asks questions about race might lack content validity, as it doesn't address other forms of prejudice
Methodological Approaches, Reliability, and Validity
- Qualitative research methods tend to have high validity and lower reliability
- Quantitative research methods tend to have lower validity and higher reliability
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